Various X-ray baggage scanning systems are known for detecting the presence of explosives and other prohibited items in baggage, or luggage, prior to loading the baggage onto a commercial aircraft. A common technique of measuring a material's density is to expose the material to X-rays and to measure the amount of radiation absorbed by the material, the absorption being indicative of the density. Since many explosive materials may be characterized by a range of densities differentiable from that of other items typically found in baggage, explosives are generally amenable to detection by X-ray equipment.
Most X-ray baggage scanning systems in use today are of the “line scanner” type and include a stationary X-ray source, a stationary linear detector array, and a conveyor belt for transporting baggage between the source and detector array as the baggage passes through the scanner. The X-ray source generates an X-ray beam that passes through and is partially attenuated by the baggage and is then received by the detector array. During each measuring interval the detector array generates data representative of the integral of density of the planar segment of the baggage through which the X-ray beam passes, and this data is used to form one or more raster lines of a two-dimensional image. As the conveyor belt transports the baggage past the stationary source and detector array, the scanner generates a two-dimensional image representative of the density of the baggage, as viewed by the stationary detector array. The density image is typically displayed for analysis by a human operator.
Techniques using dual energy X-ray sources are known for providing additional information about a material's characteristics, beyond solely a density measurement. Techniques using dual energy X-ray sources involve measuring the X-ray absorption characteristics of a material for two different energy levels of X-rays. Depending upon the calibration of the scanner, dual energy measurements provide an indication of dual parameters of the material being scanned; for example, at one calibration setting, the dual parameters can be chosen to be the material's atomic number and the material's density. At another calibration setting, the dual parameters can be chosen to be the material's Photoelectric coefficients and the material's Compton coefficients. At yet another calibration setting, the dual parameters can be chosen to be an amount of a first material present (e.g., plastic) and an amount of a second material present (e.g., aluminum). Dual energy X-ray techniques for energy-selective reconstruction of X-ray Computer Tomography (hereinafter referred to as CT) images are described, for example, in Robert E. Alvarez and Albert Macovski, “Energy-selective Reconstructions in X-ray Computerized Tomography”, Phys. Med. Biol. 1976, Vol. 21, No. 5, 733–744; and U.S. Pat. Nos. 4,029,963 and 5,132,998. One algorithm used to generate such dual parameters from dual energy X-ray projection data is known as the Alvarez/Macovski Algorithm (hereinafter referred to as AMA).
One proposed use for such dual energy techniques has been in connection with a baggage scanner for detecting the presence of explosives in baggage. Explosive materials are generally characterized by a known range of atomic numbers and are therefore amenable to detection by such dual energy X-ray sources. One such dual energy source is described in U.S. Pat. No. 5,661,774, entitled “Improved Dual Energy Power Supply.”
Plastic explosives present a particular challenge to baggage scanning systems because, due to their moldable nature, plastic explosives may be formed into geometric shapes that are difficult to detect. Most explosives capable of significantly damaging an aircraft are sufficiently large in length, width, and height so as to be readily detectable by an X-ray scanner system regardless of the explosive's orientation within the baggage. However, a plastic explosive powerful enough to damage an aircraft may be formed into a relatively thin sheet that is extremely small in one dimension and is relatively large in the other two dimensions. The detection of plastic explosives may be difficult because it may be difficult to see the explosive material in the image, particularly when the material is disposed so that the thin sheet is perpendicular to the direction of the X-ray beam as the sheet passes through the system.
Thus, detection of suspected baggage requires very attentive operators. The requirement for such attentiveness can result in greater operator fatigue, and fatigue as well as any distractions can result in a suspected bag passing through the system undetected. Accordingly, a great deal of effort has been made to design a better baggage scanner. Such designs, for example, have been described in U.S. Pat. No. 4,759,047 (Donges et al.); U.S. Pat. No. 4,884,289 (Glockmann et al.); U.S. Pat. No. 5,132,988 (Tsutsui et al.); U.S. Pat. No. 5,182,764 (Peschmann et al.); U.S. Pat. No. 5,247,561 (Kotowski); U.S. Pat. No. 5,319,547 (Krug et al.); U.S. Pat. No. 5,367,552 (Peschmann et al.); U.S. Pat. No. 5,490,218 (Krug et al.) and German Offenlegungsschrift DE 31 503 06 A1 (Heimann GmbH).
At least one of these designs, described in U.S. Pat. No. 5,182,764 (Peschmann et al.) and U.S. Pat. No. 5,367,552 (Peschmann et al.) (hereinafter the '764 and '552 patents), has been commercially developed and is referred to hereinafter as the “Invision Machine.” The Invision Machine includes a CT scanner of the third generation type, which typically includes an X-ray source and an X-ray detector system secured respectively to diametrically opposite sides of an annular-shaped platform or disk. The disk is rotatably mounted within a gantry support so that in operation the disk continuously rotates about a rotation axis while X-rays pass from the source through an object positioned within the opening of the disk to the detector system.
The detector system can include a linear array of detectors disposed as a single row in the shape of a circular arc having a center of curvature at the focal spot of the X-ray source, i.e., the point within the X-ray source from which the X-rays emanate. The X-ray source generates a fan shaped beam, or fan beam, of X-rays that emanates from the focal spot, passes through a planar imaging field, and is received by the detectors. The CT scanner includes a coordinate system defined by X-, Y- and Z-axes, wherein the axes intersect and are all normal to one another at the center of rotation of the disk as the disk rotates about the rotation axis. This center of rotation is commonly referred to as the “isocenter.” The Z-axis is defined by the rotation axis and the X- and Y-axes are defined by and lie within the planar imaging field. The fan beam is thus defined as the volume of space defined between a point source, i.e., the focal spot, and the receiving surfaces of the detectors of the detector array exposed to the X-ray beam. Because the dimension of the receiving surfaces of the linear array of detectors is relatively small in the Z-axis direction the fan beam is designed to be relatively thin in the Z-axis direction. Each detector generates an output signal representative of the intensity of the X-rays incident on that detector. Since the X-rays are partially attenuated by all the mass in their path, the output signal generated by each detector is representative of the density of all the mass disposed in the imaging field between the X-ray source and that detector.
As the disk rotates, the detector array is periodically sampled, and for each measuring interval each of the detectors in the detector array generates an output signal representative of the density of a portion of the object being scanned during that interval. The collection of all of the output signals generated by all the detectors in a single row of the detector array for any measuring interval is referred to as a “projection,” or equivalently as a “view,” and the angular orientation of the disk (and the corresponding angular orientations of the X-ray source and the detector array) during generation of a projection is referred to as the “projection angle.” At each projection angle, the path of the X-rays from the focal spot to each detector, called a “ray,” increases in cross section from a point source to the receiving surface area of the detector, and thus is thought to magnify the density measurement because the receiving surface area of the detector area is larger than any cross sectional area of the object through which the ray passes.
As the disk rotates around the object being scanned, the scanner generates a plurality of projections at a corresponding plurality of projection angles. Using well known algorithms a CT image of the object may be generated from all the projection data collected at each of the projection angles. The CT image is representative of the density of a two dimensional “slice” of the object through which the fan beam has passed during the rotation of the disk through the various projection angles. The resolution of the CT image is determined in part by the width of the receiving surface area of each detector in the plane of the fan beam, the width of the detector being defined herein as the dimension measured in the same direction as the width of the fan beam, while the length of the detector is defined herein as the dimension measured in a direction normal to the fan beam parallel to the rotation or Z-axis of the scanner. In general, the resolution of the CT image is inversely proportional to the width of the receiving surface of each detector in the plane of the fan beam.
FIGS. 1, 2 and 3 show perspective, end cross-sectional and radial cross-sectional views, respectively, of a typical baggage scanning system 100, which includes a conveyor system 110 for continuously conveying baggage or luggage 112 in a direction indicated by arrow 114 through a central aperture of a CT scanning system 120. The conveyor system includes motor driven belts for supporting the baggage. Conveyer system 110 is illustrated as including a plurality of individual conveyor sections 122; however, other forms of conveyor systems may be used.
The CT scanning system 120 includes an annular shaped rotating platform, or disk, 124 disposed within a gantry support 125 for rotation about a rotation axis 127 (shown in FIG. 3) that is preferably parallel to the direction of travel 114 of the baggage 112. Disk 124 is driven about rotation axis 127 by any suitable drive mechanism, such as a belt 116 and motor drive system 118, or other suitable drive mechanism, such as the one described in U.S. Pat. No. 5,473,657 issued Dec. 5, 1995 to Gilbert McKenna, entitled “X-ray Tomographic Scanning System,” which is assigned to the present assignee and which is incorporated herein in its entirety by reference. Rotating platform 124 defines a central aperture 126 through which conveyor system 110 transports the baggage 112.
The system 120 includes an X-ray tube 128 and a detector array 130 which are disposed on diametrically opposite sides of the platform 124. The detector array 130 can be a two-dimensional array such as the array described in U.S. Pat. No. 6,091,795 entitled, “Area Detector Array for Computed Tomography Scanning System.” The system 120 further includes a data acquisition system (DAS) 134 for receiving and processing signals generated by detector array 130, and an X-ray tube control system 136 for supplying power to, and otherwise controlling the operation of, X-ray tube 128. The system 120 is also preferably provided with a computerized system (not shown) for processing the output of the data acquisition system 134 and for generating the necessary signals for operating and controlling the system 120. The computerized system can also include a monitor for displaying information including generated images. System 120 also includes shields 138, which may be fabricated from lead, for example, for preventing radiation from propagating beyond gantry 125.
The X-ray tube 128 may generate a pyramidically shaped beam, often referred to as a “cone beam,” 132 of X-rays that pass through a three dimensional imaging field, through which conveying system 110 transports baggage 112. After passing through the baggage disposed in the imaging field, detector array 130 receives cone beam 132 and generates signals representative of the densities of exposed portions of baggage 112. The beam therefore defines a scanning volume of space. Platform 124 rotates about its rotation axis 127, thereby transporting X-ray source 128 and detector array 130 in circular trajectories about baggage 112 as the conveyor system 110 continuously transports baggage through central aperture 126, so as to generate a plurality of projections at a corresponding plurality of projection angles.
Pre-reconstruction analysis, post-reconstruction analysis and multiple projection/non-CT analysis are three prior art techniques generally recognized for using dual energy X-ray sources in materials analysis (e.g., in a baggage scanner for detecting the presence of explosives in baggage). In pre-reconstruction analysis, the signal flow is as shown in FIG. 4. The scanner 120 is typically similar to the one shown in FIG. 1 and has an X-ray source capable of producing a fan beam at two distinct energy levels (i.e., dual energy). The DAS 134 gathers signals generated by detector array 130 at discrete angular positions of the rotating platform 124, and passes the signals to the pre-processing element 206. The pre-processing element 206 re-sorts the data it receives from the DAS 134 in order to optimize the sequence for the subsequent mathematical processing. The pre-processing element 206 also corrects the data from the DAS 134 for detector temperature, intensity of the primary beam, gain and offset, and other deterministic error factors. Finally, the pre-processing element 206 extracts data corresponding to high-energy views and routes it to a high energy channel path 208, and routes the data corresponding to low-energy views to a low energy path 210.
The projection computer 212 receives the projection data on the high energy path 208 and the low energy path 210 and performs Alvarez/Macovski Algorithm processing to produce a first stream of projection data 214 which is dependent on a first parameter of the material being scanned and a second stream of projection data 216 which is dependent on a second parameter of the material scanned. The first parameter is often the atomic number and the second parameter is often material density, although other parameters may be selected. A first reconstruction computer 218 receives the first stream of projection data 214 and generates a CT image from the series of projections corresponding to the first material parameter. A second reconstruction computer 220 receives the second stream of projection data 216 and generates a CT image from the series projections corresponding to the second material parameter.
In post-reconstruction analysis, the signal flow is as shown in FIG. 5. As is described herein for pre-processing analysis, a pre-processing element 206 receives data from a DAS 134, performs several operations upon the data, then routes the data corresponding to high-energy views to a high energy path 208 and routes the data corresponding to low-energy views to a low energy path 210. A first reconstruction computer 218 receives the projection data from the high-energy path 208 and generates a CT image corresponding to the high-energy series of projections. A second reconstruction computer 220 receives the projection data from the low-energy path 210 and generates a CT image corresponding to the low-energy series of projections. A projection computer 212 receives the high energy CT data 222 and the low-energy CT data 224 and performs AMA processing to produce CT data 226 which is dependent on a first parameter of the material being scanned and a second stream of projection data 228 which is dependent on a second parameter of the material scanned.
Various approaches have been used for decomposition of projection data (P). For example, the AMA non-linear equation approximates the integral equations by a second order power series in Ac and Ap, where Ac represents the Compton line integral and Ap represents the Photoelectric line integral. The line integral equations are given as:PL=b0+b1Ac+b2Ap+b3AcAp+b4Ac2+b5Ap2 PH=c0+c1Ac+c2Ap+c3AcAp+c4Ac2+c5Ap2  (1)
The coefficients bi and ci are determined through a calibration procedure as follows. By measuring the projections values of the combination of various thickness of two known materials, a set of equations in the form of Equation 1 can be formed. Since PL, PH, Ac and Ap are known for the calibration data, the coefficients are calculated using a polynomial least squares fitting algorithm.
Once the coefficients bi and ci are determined, the decomposition of the Compton (Ac) and Photoelectric (Ap) images from projections PL, PH is accomplished by solving Equation 1 using the Newton-Raphson method for each pixel in the image.
The disadvantage of the method is that it is computationally slow and potentially unstable because the iteration can diverge if the initial guess to the solution of Equation 1 is not sufficiently close to the true solution. Therefore, the method is susceptible to noise and to extrapolation outside the region of calibration causing large approximation errors.
Another prior art method of performing decomposition is the direct approximation method, discussed in L. A. Lehmann, R. E. Alvarez, A. Macovski, W. R. Brody, N. J. Pelc, S. J. Riederer, and A. L. Hall, Generalized Image Combinations In Dual KVP Digital Radiography, Med. Phys. 8, 659–667 (1981). In the direct approximation method, Ac and Ap are expressed as a power series in PL, PH Ac=d0+d1PL+d2PH+d3PLPH+d4PL2+d5PH2 Ap=e0+e1PL+e2PH+e3PLPH+e4PL2+e5PH2  (2)
As in the non-linear equation method, the coefficients di and ei are determined through a calibration procedure, as follows. By measuring the projections values of the combination of various thicknesses of two known materials, one obtains a set of equations in the form of Equation 1. Since PL, PH, Ac and Ap are known for the calibration data, the coefficients are calculated using a polynomial least squares fitting algorithm. For a given pair of projections (PL, PH), Ac and Ap are can be calculated directly from Equation 2.
The direct decomposition method avoids the issues of iterative convergence of the non-linear equations. However, the method has the disadvantage that it requires a large number of polynomial terms in Equation 2 in order to obtain accuracy over an extended range of projection values. The use of higher order polynomials then introduces a ripple which can be controlled only by obtaining a large number of calibration points.
In yet another prior art method, decomposition is accomplished using iso-transmission lines, described K. Chuang and H. K. Huang, A Fast Dual-Energy Computational Method Using Isotransmission Lines and Tables, Med. Phys. 14, 186–192 (1987). According to this method, for a given projection value, an iso-transmission line is represented by a linear equation in two basis functions, wherein the thickness of aluminum and plastic (as examples) is given by tAL and tPl, respectively, as:PL=atAl+btPl PH=dtAl+etPl  (3)where PL and PH are the high and low energy projections and a, b, d, e are regression coefficients that are proportional to the attenuation coefficients of aluminum and plastic. The solution of Equation 3 determines the aluminum and plastic combination (tAl, tPl) that determines (PL, PH).
The regression coefficients are generated from high and low energy calibration tables. The tables contain regression coefficients generated for pre-defined projection values. The pre-defined projections are generated by scanning known thicknesses of aluminum and plastic. For a given projection value, the regression coefficients are generated by interpolation between the closest two pre-defined coefficients stored in the table.
The iso-transmission line method requires a large amount of calibration data in order to generate the regression coefficients a, b, d, e. Further, the iso-transmission lines become increasingly non-linear as the projection value increases. In such a situation, the linear equations are not valid and the method causes large approximation errors.
Other prior methods for dual energy decomposition also suffer from shortcomings, as discussed in H. N. Cardinal and A, Fenster, An Accurate Method For Direct Dual Energy Calibration and Decomposition by, Med. Phys. 17, 327–341 (1990). As an example, the direct decomposition algorithm produces incomplete separation of objects, as determined visually. Additionally, the direct decomposition algorithm also introduces artifacts in the decomposed images of scanner data. The artifacts are primarily produced by approximation errors, sensitivity to noise and the lack of handling of exceptions in the input projection data. In addition, the algorithm requires a calibration procedure that is complicated, time consuming and prone to measurement errors, which propagate through the decomposition procedure to be manifested as artifacts in images.